There is increasing need within a variety of fields to be able to determine very rapidly whether or not a particular sample record already exists within a large database, and if so to identify one or more matches. One particular field is biometrics, in which the requirement is to determine whether or not the individual who has provided a particular biometric sample is already in the database.
Databases of the type described can be extremely large, and it may be impractical to attempt a full match analysis between the sample record and every one of the records within the database. In order to reduce the computational workload, a variety of pre-screening processes are in use, but many of these have very restricted fields of application since they often rely upon specific peculiarities of the matching algorithm or of the data that are to be matched.
An issue that arises particularly with the matching of biometric data, although it occurs in other applications as well, is that by their nature biometric measurements are often not precisely reproducible. For example, repeated biometric measurements derived from the iris of a particular individual are likely to vary somewhat, not least because the extent of iris occlusion by the eyelid and eyelashes will vary between images. As a result, biometric matching normally relies upon the concept of an approximate or “fuzzy” match, rather than on an exact match.
A typical scenario is the need to determine whether a particular individual exists within a large database of individuals. For example, we may have an iris scan of an individual and want to know whether a national security database already contains one or more iris scans of the same individual. Because the sample iris scan and the stored iris scans are unlikely to be identical in all respects, one way of achieving the necessary “fuzzy” match is to search over a region. Having converted both the sample and the stored records into codes, according to some predefined protocol, we can attempt to find a match between a stored record and any code within a region which we consider to be sufficiently close to the sample code. Alternatively, we may attempt a match between the sample code and any code within a search region which is sufficiently close to one of the stored codes. In either case, the need to search over a region of codes when doing the fuzzy match may significantly slow down the matching process.
The present invention is provided to solve the problems discussed above and other problems, and to provide advantages and aspects not provided by prior database systems of this type. A full discussion of the features and advantages of the present invention is deferred to the following detailed description, which proceeds with reference to the accompanying drawings.